A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation

Abstract

The detection of ligand-binding sites is often the starting point for protein function identification and drug discovery. Because of inaccuracies in predicted protein structures, extant binding pocket-detection methods are limited to experimentally solved structures. Here, FINDSITE, a method for ligand-binding site prediction and functional annotation based on binding-site similarity across groups of weakly homologous template structures identified from threading, is described. For crystal structures, considering a cutoff distance of 4 A as the hit criterion, the success rate is 70.9% for identifying the best of top five predicted ligand-binding sites with a ranking accuracy of 76.0%. Both high prediction accuracy and ability to correctly rank identified binding sites are sustained when approximate protein models (<35% sequence identity to the closest template structure) are used, showing a 67.3% success rate with 75.5% ranking accuracy. In practice, FINDSITE tolerates structural inaccuracies in protein models up to a rmsd from the crystal structure of 8-10 A. This is because analysis of weakly homologous protein models reveals that about half have a rmsd from the native binding site <2 A. Furthermore, the chemical properties of template-bound ligands can be used to select ligand templates associated with the binding site. In most cases, FINDSITE can accurately assign a molecular function to the protein model.

Fig. 1.

Overview of the FINDSITE prediction methodology. Details are given in Materials and Methods.

Fig. 2.

Performance of FINDSITE and LIGSITE^CSC compared with randomly selected patches on a target protein surface using target crystal structures (A) and TASSER models (B). The results are presented as the cumulative fraction of proteins with a distance between the center of mass of a ligand in the native complex and the center of the best of top five predicted binding sites, less than or equal to the distance displayed on the x axis and the rank of the best pocket selected from the top five predictions (Inset).

Fig. 3.

Average distance between the native ligand center of mass upon superposition of a protein model onto the protein–ligand crystal complex with respect to the binding residues and the center of predicted binding pocket. The accuracy is presented for decreasing quality of TASSER models used in the prediction procedure, expressed by the global rmsd from the crystal structure. The solid line is the local rmsd calculated for the ligand-binding regions.

Fig. 4.

Cumulative distribution of enrichment factors resulting from the ligand-based virtual screening experiment against the KEGG compound library using ligand templates selected by FINDSITE. Target proteins are divided into the two subsets with respect to the accuracy of binding pocket prediction (the distance between the top-ranked pocket and the center of mass of the native ligand ≤4 and >4 Å).